Evidence map›Paper›PMID 37247214›Full record

ArticleJournal of medical Internet research2023

Impacts of Symptom Checkers for Laypersons' Self-diagnosis on Physicians in Primary Care: Scoping Review.

Natalia Radionova, Eylem Ög, Anna-Jasmin Wetzel, Monika A Rieger, Christine Preiser

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Review
  5. Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Natalia RadionovaInstitute of Occupational Medicine, Social Medicine and Health Services Research, University Hospital Tuebingen, Tuebingen, Germany.ORCID 0000-0002-5382-0876
Eylem ÖgInstitute of Occupational Medicine, Social Medicine and Health Services Research, University Hospital Tuebingen, Tuebingen, Germany.ORCID 0009-0008-7100-9359
Anna-Jasmin WetzelInstitute for General Practice and Interprofessional Care, University Hospital Tuebingen, Tuebingen, Germany.ORCID 0000-0002-7127-5867
Monika A RiegerInstitute of Occupational Medicine, Social Medicine and Health Services Research, University Hospital Tuebingen, Tuebingen, Germany.ORCID 0000-0002-7855-3663
Christine PreiserInstitute of Occupational Medicine, Social Medicine and Health Services Research, University Hospital Tuebingen, Tuebingen, Germany.ORCID 0000-0002-5549-6336

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSymptom checkers (SCs) for laypersons' self-assessment and preliminary self-diagnosis are widely used by the public. Little is known about the impact of these tools on health care professionals (HCPs) in primary care and their work. This is relevant to understanding how technological changes might affect the working world and how this is linked to work-related psychosocial demands and resources for HCPs.

objectiveThis scoping review aimed to systematically explore the existing publications on the impacts of SCs on HCPs in primary care and to identify knowledge gaps.

methodsWe used the Arksey and O'Malley framework. We based our search string on the participant, concept, and context scheme and searched PubMed (MEDLINE) and CINAHL in January and June 2021. We performed a reference search in August 2021 and a manual search in November 2021. We included publications of peer-reviewed journals that focused on artificial intelligence- or algorithm-based self-diagnosing apps and tools for laypersons and had primary care or nonclinical settings as a relevant context. The characteristics of these studies were described numerically. We used thematic analysis to identify core themes. We followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist to report the study.

resultsOf the 2729 publications identified through initial and follow-up database searches, 43 full texts were screened for eligibility, of which 9 were included. Further 8 publications were included through manual search. Two publications were excluded after receiving feedback in the peer-review process. Fifteen publications were included in the final sample, which comprised 5 (33%) commentaries or nonresearch publications, 3 (20%) literature reviews, and 7 (47%) research publications. The earliest publications stemmed from 2015. We identified 5 themes. The theme finding prediagnosis comprised the comparison between SCs and physicians. We identified the performance of the diagnosis and the relevance of human factors as topics. In the theme layperson-technology relationship, we identified potentials for laypersons' empowerment and harm through SCs. Our analysis showed potential disruptions of the physician-patient relationship and uncontested roles of HCPs in the theme (impacts on) physician-patient relationship. In the theme impacts on HCPs' tasks, we described the reduction or increase in HCPs' workload. We identified potential transformations of HCPs' work and impacts on the health care system in the theme future role of SCs in health care.

conclusionsThe scoping review approach was suitable for this new field of research. The heterogeneity of technologies and wordings was challenging. We identified research gaps in the literature regarding the impact of artificial intelligence- or algorithm-based self-diagnosing apps or tools on the work of HCPs in primary care. Further empirical studies on HCPs' lived experiences are needed, as the current literature depicts expectations rather than empirical findings.

Indexed as

Artificial IntelligencePhysiciansHealth PersonnelHumansPhysician-Patient RelationsPrimary Health CareAI-based technologyartificial intelligence–based technologygeneral practicemHealthmobile healthmobile phonescoping reviewself-diagnosissymptom checkers

Identifiers

PMID37247214
PMCPMC10262026

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.